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Empirically-driven hierarchical classification of stock keeping units

Author

Listed:
  • Bacchetti, A.
  • Plebani, F.
  • Saccani, N.
  • Syntetos, A.A.

Abstract

This paper proposes a hierarchical multi-criteria classification method developed for inventory management purposes and applied in a case study of the spare parts business of a household appliance manufacturer. The classification method is built on the basis of SIX dimensions, resulting in 12 different classes of spare parts, for which differentiated forecasting and inventory policies are proposed and tested. The results of our simulation study demonstrate the reduction of the total logistics costs by about 20% whilst still achieving the specified target service level for each class. Even more importantly, the proposed approach is simple enough to be understood and applied by company managers, thus increasing the probability of its adoption (in the same or similar fashion) in other real world settings.

Suggested Citation

  • Bacchetti, A. & Plebani, F. & Saccani, N. & Syntetos, A.A., 2013. "Empirically-driven hierarchical classification of stock keeping units," International Journal of Production Economics, Elsevier, vol. 143(2), pages 263-274.
  • Handle: RePEc:eee:proeco:v:143:y:2013:i:2:p:263-274
    DOI: 10.1016/j.ijpe.2012.06.010
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    References listed on IDEAS

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    1. A A Syntetos & J E Boylan & J D Croston, 2005. "On the categorization of demand patterns," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(5), pages 495-503, May.
    2. Ng, Wan Lung, 2007. "A simple classifier for multiple criteria ABC analysis," European Journal of Operational Research, Elsevier, vol. 177(1), pages 344-353, February.
    3. Zhou, Peng & Fan, Liwei, 2007. "A note on multi-criteria ABC inventory classification using weighted linear optimization," European Journal of Operational Research, Elsevier, vol. 182(3), pages 1488-1491, November.
    4. Huiskonen, Janne, 2001. "Maintenance spare parts logistics: Special characteristics and strategic choices," International Journal of Production Economics, Elsevier, vol. 71(1-3), pages 125-133, May.
    5. Syntetos, A.A. & Babai, M.Z. & Davies, J. & Stephenson, D., 2010. "Forecasting and stock control: A study in a wholesaling context," International Journal of Production Economics, Elsevier, vol. 127(1), pages 103-111, September.
    6. Nenes, George & Panagiotidou, Sofia & Tagaras, George, 2010. "Inventory management of multiple items with irregular demand: A case study," European Journal of Operational Research, Elsevier, vol. 205(2), pages 313-324, September.
    7. Gajpal, Prem Prakash & Ganesh, L. S. & Rajendran, Chandrasekharan, 1994. "Criticality analysis of spare parts using the analytic hierarchy process," International Journal of Production Economics, Elsevier, vol. 35(1-3), pages 293-297, June.
    8. Syntetos, Aris A. & Nikolopoulos, Konstantinos & Boylan, John E. & Fildes, Robert & Goodwin, Paul, 2009. "The effects of integrating management judgement into intermittent demand forecasts," International Journal of Production Economics, Elsevier, vol. 118(1), pages 72-81, March.
    9. Yamashina, H., 1989. "The service parts control problem," Engineering Costs and Production Economics, Elsevier, vol. 16(3), pages 195-208, June.
    10. Porras, Eric & Dekker, Rommert, 2008. "An inventory control system for spare parts at a refinery: An empirical comparison of different re-order point methods," European Journal of Operational Research, Elsevier, vol. 184(1), pages 101-132, January.
    11. Petrovic, D. & Petrovic, R., 1992. "SPARTA II: Further development in an expert system for advising on stocks of spare parts," International Journal of Production Economics, Elsevier, vol. 24(3), pages 291-300, March.
    12. Boylan, J.E. & Syntetos, A.A., 2007. "The accuracy of a Modified Croston procedure," International Journal of Production Economics, Elsevier, vol. 107(2), pages 511-517, June.
    13. Zied Babai, M. & Syntetos, Aris A. & Teunter, Ruud, 2010. "On the empirical performance of (T, s, S) heuristics," European Journal of Operational Research, Elsevier, vol. 202(2), pages 466-472, April.
    14. Kalchschmidt, Matteo & Zotteri, Giulio & Verganti, Roberto, 2003. "Inventory management in a multi-echelon spare parts supply chain," International Journal of Production Economics, Elsevier, vol. 81(1), pages 397-413, January.
    15. John E. Boylan & Aris A. Syntetos, 2008. "Forecasting for Inventory Management of Service Parts," Springer Series in Reliability Engineering, in: Complex System Maintenance Handbook, chapter 20, pages 479-506, Springer.
    16. Jouni, Paakki & Huiskonen, Janne & Pirttilä, Timo, 2011. "Improving global spare parts distribution chain performance through part categorization: A case study," International Journal of Production Economics, Elsevier, vol. 133(1), pages 164-171, September.
    17. Murthy, D. N. P. & Solem, O. & Roren, T., 2004. "Product warranty logistics: Issues and challenges," European Journal of Operational Research, Elsevier, vol. 156(1), pages 110-126, July.
    18. J E Boylan & A A Syntetos & G C Karakostas, 2008. "Classification for forecasting and stock control: a case study," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(4), pages 473-481, April.
    19. A H C Eaves & B G Kingsman, 2004. "Forecasting for the ordering and stock-holding of spare parts," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(4), pages 431-437, April.
    20. Bacchetti, Andrea & Saccani, Nicola, 2012. "Spare parts classification and demand forecasting for stock control: Investigating the gap between research and practice," Omega, Elsevier, vol. 40(6), pages 722-737.
    21. A A Syntetos & M Z Babai & Y Dallery & R Teunter, 2009. "Periodic control of intermittent demand items: theory and empirical analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(5), pages 611-618, May.
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    Cited by:

    1. Hu, Qiwei & Boylan, John E. & Chen, Huijing & Labib, Ashraf, 2018. "OR in spare parts management: A review," European Journal of Operational Research, Elsevier, vol. 266(2), pages 395-414.
    2. Sheikh-Zadeh, Alireza & Rossetti, Manuel D. & Scott, Marc A., 2021. "Performance-based inventory classification methods for large-Scale multi-echelon replenishment systems," Omega, Elsevier, vol. 101(C).
    3. Rego, José Roberto do & Mesquita, Marco Aurélio de, 2015. "Demand forecasting and inventory control: A simulation study on automotive spare parts," International Journal of Production Economics, Elsevier, vol. 161(C), pages 1-16.

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